David Kelley
Principal Investigator
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolDavid Kelley is a Principal Investigator at Calico Life Sciences with 11 years of experience developing machine learning methods to study gene regulation. He combines a PhD in Computer Science with postdoctoral training in stem cell biology to translate deep learning advances—especially convolutional neural networks—into predictive models of regulatory activity. At Calico he progressed from Bioinformatics Scientist to lead investigator, contributing backend ML engineering to notable open-source projects like Basenji that predict sequential regulatory activity. Based in San Francisco, he balances rigorous academic foundations with production-focused engineering, integrating model architecture and training pipelines to drive biological insight. An often-overlooked strength is his fluency across research and software domains, enabling him to move ideas from notebooks to scalable code.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Science (BS) Computer Science, Bachelor of Science (BS) Computer Science at Syracuse UniversityDoctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at University of Maryland
Github Skills (11)
mask-rcnn10
faster-rcnn10
machine-learning10
tensorflow10
architectures10
python10
modeling10
architecture10
normalization9
normalizing9
normalize9
Programming languages (7)
Github contributions (5)
calico/basenji
Jun 2016 - Jan 2023
Sequential regulatory activity predictions with deep convolutional neural networks.
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:8 releases, 1935 commits, 24 PRs in 6 years 8 months
Contributions summary:David implemented new syntax for the project and integrated code differences. They worked on convolutional neural networks (CNNs) and model architecture, and integrated a variety of techniques demonstrating expertise in machine learning principles. The changes involve files related to model training and general architecture, suggesting a developer with an ML engineering and backend engineering focus.
regulatorydeep-learningconvolutionalneural-networkspredictions
davek44/Basset
Aug 2015 - Sep 2020
Convolutional neural network analysis for predicting DNA sequence activity.
Contributions:1 release, 422 commits, 3 PRs in 5 years 1 month
sequencednadna-sequenceconvolutional-neural-networkconvolutional
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.